• 1.

    Young M, Wolfheim C, Marsh DR, Hammamy D, 2012. World Health Organization/United Nations Children's Fund joint statement on integrated community case management: an equity-focused strategy to improve access to essential treatment services for children. Am J Trop Med Hyg 87 (Suppl): 610.

    • Search Google Scholar
    • Export Citation
  • 2.

    UN Interagency Group for Child Mortality Estimation, 2014. Levels and Trends in Child Mortality New York, NY: UNICEF.

  • 3.

    Marsh DR, Hamer DH, Pagnoni F, Peterson S, 2012. Introduction to a special supplement: evidence for the implementation, effects, and impact of the integrated community case management strategy to treat childhood infection. Am J Trop Med Hyg 87 (Suppl): 25.

    • Search Google Scholar
    • Export Citation
  • 4.

    Lewin S, Munabi-Babigumira S, Glenton C, Daniels K, Bosch-Capblanch X, van Wyk BE, Odgaard-Jensen J, Johansen M, Aja GN, Zwarenstein M, Scheel IB, 2010. Lay health workers in primary and community health care for maternal and child health and the management of infectious diseases. Cochrane Database Syst Rev (3) CD004015.

    • Search Google Scholar
    • Export Citation
  • 5.

    Sazawal S, Black RE, 1992. Meta-analysis of intervention trials on case-management of pneumonia in community settings. Lancet 340: 528533.

    • Search Google Scholar
    • Export Citation
  • 6.

    Sazawal S, Black RE; Pneumonia Case Management Trials Group, 2003. Effect of pneumonia case management on mortality in neonates, infants, and preschool children: a meta-analysis of community-based trials. Lancet Infect Dis 3: 547556.

    • Search Google Scholar
    • Export Citation
  • 7.

    Hamer DH, Brooks ET, Semrau K, Pilingana P, MacLeod WB, Siazeele K, Sabin LL, Thea DM, Yeboah-Antwi K, 2012. Quality and safety of integrated community case management of malaria using rapid diagnostic tests and pneumonia by community health workers. Pathog Glob Health 106: 3239.

    • Search Google Scholar
    • Export Citation
  • 8.

    Seidenberg PD, Hamer DH, Iyer H, Pilingana P, Siazeele K, Hamainza B, MacLeod WB, Yeboah-Antwi K, 2012. Impact of integrated community case management on health-seeking behavior in rural Zambia. Am J Trop Med Hyg 87 (Suppl): 105110.

    • Search Google Scholar
    • Export Citation
  • 9.

    Kalyango JN, Rutebemberwa E, Alfven T, Ssali S, Peterson S, Karamagi C, 2012. Performance of community health workers under integrated community case management of childhood illnesses in eastern Uganda. Malar J 11: 282.

    • Search Google Scholar
    • Export Citation
  • 10.

    Kalyango JN, Alfven T, Peterson S, Mugenyi K, Karamagi C, Rutebemberwa E, 2013. Integrated community case management of malaria and pneumonia increases prompt and appropriate treatment for pneumonia symptoms in children under five years in eastern Uganda. Malar J 12: 340.

    • Search Google Scholar
    • Export Citation
  • 11.

    Kalyango JN, Rutebemberwa E, Karamagi C, Mworozi E, Ssali S, Alfven T, Peterson S, 2013. High adherence to antimalarials and antibiotics under integrated community case management of illness in children less than five years in eastern Uganda. PLoS One 8: e60481.

    • Search Google Scholar
    • Export Citation
  • 12.

    Mugeni C, Levine AC, Munyaneza RM, Mulindahabi E, Cockrell HC, Glavis-Bloom J, Nutt CT, Wagner CM, Gaju E, Rukundo A, Habimana JP, Karema C, Ngabo F, Binagwaho A, 2014. Nationwide implementation of integrated community case management of childhood illness in Rwanda. Glob Health Sci Pract 2: 328341.

    • Search Google Scholar
    • Export Citation
  • 13.

    Kelly JM, Osamba B, Garg RM, Hamel MJ, Lewis JJ, Rowe SY, Rowe AK, Deming MS, 2001. Community health worker performance in the management of multiple childhood illnesses: Siaya District, Kenya, 1997–2001. Am J Public Health 91: 16171624.

    • Search Google Scholar
    • Export Citation
  • 14.

    Nsona H, Mtimuni A, Daelmans B, Callaghan-Koru JA, Gilroy K, Mgalula L, Kachule T, Zamasiya T, 2012. Scaling up integrated community case management of childhood illness: update from Malawi. Am J Trop Med Hyg 87 (Suppl): 5460.

    • Search Google Scholar
    • Export Citation
  • 15.

    Chinbuah MA, Kager PA, Abbey M, Gyapong M, Awini E, Nonvignon J, Adjuik M, Aikins M, Pagnoni F, Gyapong JO, 2012. Impact of community management of fever (using antimalarials with or without antibiotics) on childhood mortality: a cluster-randomized controlled trial in Ghana. Am J Trop Med Hyg 87 (Suppl): 1120.

    • Search Google Scholar
    • Export Citation
  • 16.

    Miller NP, Amouzou A, Tafesse M, Hazel E, Legesse H, Degefie T, Victora CG, Black RE, Bryce J, 2014. Integrated community case management of childhood illness in Ethiopia: implementation strength and quality of care. Am J Trop Med Hyg 91: 424434.

    • Search Google Scholar
    • Export Citation
  • 17.

    Rasanathan K, Muñiz M, Bakshi S, Kumar M, Solano A, Kariuki W, George A, Sylla M, Nefdt R, Young M, Diaz T, 2014. Community case management of childhood illness in sub-Saharan Africa—findings from a cross-sectional survey on policy and implementation. J Glob Health 4: 020401.

    • Search Google Scholar
    • Export Citation
  • 18.

    Pallas SW, Minhas D, Pérez-Escamilla R, Taylor L, Curry L, Bradley EH, 2013. Community health workers in low-and middle-income countries: what do we know about scaling up and sustainability? Am J Public Health 103: e74e82.

    • Search Google Scholar
    • Export Citation
  • 19.

    Buchner DL, Brenner JL, Kabakyenga J, Teddy K, Maling S, Barigye C, Nettel-Aguirre A, Singhal N, 2014. Stakeholders' perceptions of integrated community case management by community health workers: a post-intervention qualitative study. PLoS One 9: e98610.

    • Search Google Scholar
    • Export Citation
  • 20.

    Nanyonjo A, Nakirunda M, Makumbi F, Tomson G, Kallander K; inSCALE Study Group, 2012. Community acceptability and adoption of integrated community case management in Uganda. Am J Trop Med Hyg 87 (Suppl): 97104.

    • Search Google Scholar
    • Export Citation
  • 21.

    Delacollette C, Van der Stuyft P, Molima K, 1996. Using community health workers for malaria control: experience in Zaire. Bull World Health Organ 74: 423.

    • Search Google Scholar
    • Export Citation
  • 22.

    Collins D, Jarrah Z, Gilmartin C, Saya U, 2014. The costs of integrated community case management (iCCM) programs: a multi-country analysis. J Glob Health 4: 020407.

    • Search Google Scholar
    • Export Citation
  • 23.

    Nanyonjo A, Makumbi F, Etou P, Tomson GR, Kallander K; inSCALE Study Group, 2013. Perceived quality of care for common childhood illnesses: facility versus community based providers in Uganda. PLoS One 8: e79943.

    • Search Google Scholar
    • Export Citation
  • 24.

    Safran DG, Kosinski M, Tarlov AR, Rogers WH, Taira DH, Lieberman N, Ware JE, 1998. The Primary Care Assessment Survey: tests of data quality and measurement performance. Med Care 36: 728739.

    • Search Google Scholar
    • Export Citation
  • 25.

    Population Action International, 2014. Population Dynamics, Environment, and Sustainable Development in Homa Bay County Available at: http://pai.org/wp-content/uploads/2014/07/PAI_HomaBay-3.pdf. Accessed May 3, 2015.

    • Search Google Scholar
    • Export Citation
  • 26.

    Kenya National Bureau of Statistics, 2013. Nyanza Province Multiple Indicator Cluster Survey 2011, Final Report. Nairobi, Kenya: Kenya National Bureau of Statistics.

    • Search Google Scholar
    • Export Citation
  • 27.

    Bedford KJA, Sharkey AB, 2014. Local barriers and solutions to improve care-seeking for childhood pneumonia, diarrhoea and malaria in Kenya, Nigeria, and Niger: a qualitative study. PLoS One 9: e100038.

    • Search Google Scholar
    • Export Citation
  • 28.

    Health Policy Project, 2013. Homabay County: Health at a Glance. Available at: http://www.healthpolicyproject.com/pubs/291/Homa%20Bay%20County-FINAL.pdf. Accessed May 3, 2015.

    • Search Google Scholar
    • Export Citation
  • 29.

    Kenya Ministry of Health, 2013. A National Framework and Plan of Action for Implementation of Integrated Community Case Management (iCCM) in Kenya, 2013–2018. Nairobi, Kenya: Kenya Ministry of Health.

    • Search Google Scholar
    • Export Citation
  • 30.

    Otien SO, Macharia D, 2014. Factors influencing utilization of health services in Kenya: the case of Homa Bay County. IJPHS 3: 213223.

  • 31.

    Fotso JC, Mukiira C, 2012. Perceived quality of and access to care among poor urban women in Kenya and their utilization of delivery care: harnessing the potential of private clinics? Health Policy Plan 27: 505515.

    • Search Google Scholar
    • Export Citation
  • 32.

    Filmer D, Pritchett LH, 2001. Estimating wealth effects without expenditure data—or tears: an application to educational enrollments in states of India. Demography 38: 115132.

    • Search Google Scholar
    • Export Citation
  • 33.

    Zou G, 2004. A modified Poisson regression approach to prospective studies with binary data. Am J Epidemiol 159: 702706.

  • 34.

    Tanser F, Gijsbertsen B, Herbst K, 2006. Modelling and understanding primary health care accessibility and utilization in rural South Africa: an exploration using a geographical information system. Soc Sci Med 63: 691705.

    • Search Google Scholar
    • Export Citation
  • 35.

    Ensor T, 2004. Overcoming barriers to health service access: influencing the demand side. Health Policy Plan 19: 6979.

  • 36.

    Chuma J, Musimbi J, Okungu V, Goodman C, Molyneux C, 2009. Reducing user fees for primary health care in Kenya: policy on paper or policy in practice? Int J Equity Health 8: 15.

    • Search Google Scholar
    • Export Citation
  • 37.

    Opwora A, Waweru E, Toda M, Noor A, Edwards T, Fegan G, Molyneux S, Goodman C, 2015. Implementation of patient charges at primary care facilities in Kenya: implications of low adherence to user fee policy for users and facility revenue. Health Policy Plan 30: 508517.

    • Search Google Scholar
    • Export Citation
  • 38.

    Tefera W, Tesfaye H, Bekele A, Kayessa E, 2014. Factors influencing the low utilization of curative child health services in Shebedino District, Sidama Zone, Ethiopia. Ethiop Med J 52 (Suppl 3): 109117.

    • Search Google Scholar
    • Export Citation
  • 39.

    Kredo T, Adeniyi FB, Bateganya M, Pienaar ED, 2014. Task shifting from doctors to non-doctors for initiation and maintenance of antiretroviral therapy. Cochrane Database Syst Rev 7: CD007331.

    • Search Google Scholar
    • Export Citation
  • 40.

    Abel WM, Efird JT, 2013. The association between trust in health care providers and medication adherence among black women with hypertension. Front Public Health 1: 66.

    • Search Google Scholar
    • Export Citation
  • 41.

    Najjemba R, Kiapi L, Demissie SD, Gossaye T, Engida M, Ratnayake R, Degefie T, Legesse H, Lemma AF, Getachew H, Gebrie M, 2014. Integrated community case management: quality of care and adherence to medication in Beneshangul-Gumuz Region, Ethiopia. Ethiop Med J 52 (Suppl 3): 8390.

    • Search Google Scholar
    • Export Citation
  • 42.

    Hamer DH, Marsh DR, Peterson S, Pagnoni F, 2012. Integrated community case management: next steps in addressing the implementation research agenda. Am J Trop Med Hyg 87 (Suppl): 151153.

    • Search Google Scholar
    • Export Citation
  • 43.

    Kardas P, 2002. Patient compliance with antibiotic treatment for respiratory tract infections, 2002. J Antimicrob Chemother 49: 897903.

    • Search Google Scholar
    • Export Citation
  • 44.

    Mellanby AR, Newcombe RG, Rees J, Tripp JH, 2001. A comparative study of peer-led and adult-led school sex education. Health Educ Res 16: 481492.

    • Search Google Scholar
    • Export Citation
  • 45.

    Owolabi OO, Glenton C, Lewin S, Pakenham-Walsh N, 2014. Stakeholder views on the incorporation of traditional birth attendants into the formal health systems of low-and middle-income countries: a qualitative analysis of the HIFA2015 and CHILD2015 email discussion forums. BMC Pregnancy Childbirth 14: 19.

    • Search Google Scholar
    • Export Citation
  • 46.

    Rustagi AS, Manjate RM, Gloyd S, John-Stewart G, Micek M, Gimbel S, Sherr K, 2015. Perspectives of key stakeholders regarding task shifting of care for HIV patients in Mozambique: a qualitative interview-based study with Ministry of Health leaders, clinicians, and donors. Hum Resour Health 13: 18.

    • Search Google Scholar
    • Export Citation
  • 47.

    Lynam PF, Smith T, Dwyer J, 1994. Client flow analysis: a practical management technique for outpatient clinic settings. Int J Qual Health Care 6: 179186.

    • Search Google Scholar
    • Export Citation
  • 48.

    Lange S, Mwisongo A, Mæstad O, 2014. Why don't clinicians adhere more consistently to guidelines for the integrated management of childhood illness (IMCI)? Soc Sci Med 104: 5663.

    • Search Google Scholar
    • Export Citation
  • 49.

    Ameha A, Karim AM, Erbo A, Ashenafi A, Hailu M, Hailu B, Folla A, Bizuwork S, Betemariam W, 2014. Effectiveness of supportive supervision on the consistency of integrated community cases management skills of the health extension workers in 113 districts of Ethiopia. Ethiop Med J 52 (Suppl 3): 6571.

    • Search Google Scholar
    • Export Citation
  • 50.

    Ahmed HM, Mitchell M, Hedt B, 2010. National implementation of integrated management of childhood illness (IMCI): policy constraints and strategies. Health Policy 96: 128133.

    • Search Google Scholar
    • Export Citation
  • 51.

    Ajayi IO, Falade CO, Olley BO, Yusuf B, Gbotosho S, Iyiola T, Olaniyan O, Happi C, Munguti K, Pagnoni F, 2008. A qualitative study of the feasibility and community perception on the effectiveness of artemether-lumefantrine use in the context of home management of malaria in south-west Nigeria. BMC Health Serv Res 8: 119.

    • Search Google Scholar
    • Export Citation
  • 52.

    Ajayi IO, Browne EN, Garshong B, Bateganya F, Yusuf B, Agyei-Baffour P, Doamekpor L, Balyeku A, Munguti K, Cousens S, Pagnoni F, 2008. Feasibility and acceptability of artemisinin-based combination therapy for the home management of malaria in four African sites. Malar J 7: 6.

    • Search Google Scholar
    • Export Citation
  • 53.

    Akweongo P, Agyei-Baffour P, Sudhakar M, Simwaka BN, Konaté AT, Adongo PB, Browne EN, Tegegn A, Ali D, Traoré A, Amuyunzu-Nyamongo M, Pagnoni F, Barnish G, 2011. Feasibility and acceptability of ACT for the community case management of malaria inurban settings in five African sites. Malar J 10: 240.

    • Search Google Scholar
    • Export Citation
  • 54.

    Callaghan-Koru JA, Hyder AA, George A, Gilroy KE, Nsona H, Mtimuni A, Bryce J, 2012. Health workers “and managers” perceptions of the integrated community case management program for childhood illness in Malawi: the importance of expanding access to child health services. Am J Trop Med Hyg 87 (Suppl): 6168.

    • Search Google Scholar
    • Export Citation
  • 55.

    Gyimah SO, Takyi BK, Addai I, 2006. Challenges to the reproductive-health needs of African women: on religion and maternal health utilization in Ghana. Soc Sci Med 62: 29302944.

    • Search Google Scholar
    • Export Citation
  • 56.

    Addai I, 2000. Determinants of use of maternal–child health services in rural Ghana. J Biosoc Sci 32: 115.

  • 57.

    Sibeko L, Coutsoudis A, Nzuza S, Gray-Donald K, 2009. Mothers' infant feeding experiences: constraints and supports for optimal feeding in an HIV-impacted urban community in South Africa. Public Health Nutr 12: 1983.

    • Search Google Scholar
    • Export Citation

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Perceived Quality of Care of Community Health Worker and Facility-Based Health Worker Management of Pneumonia in Children Under 5 Years in Western Kenya: A Cross-Sectional Multidimensional Study

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  • School of Medicine, University of California, San Francisco, San Francisco, California; Kenya Medical Research Institute, Nairobi, Kenya; United Nations International Children's Emergency Fund, New York, New York; Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, California

Integrated community case management (iCCM) programs that train lay community health workers (CHWs) in the diagnosis and treatment of diarrhea, malaria, and pneumonia have been increasingly adopted throughout sub-Saharan Africa to provide services in areas where accessibility to formal public sector health services is low. One important aspect of successful iCCM programs is the acceptability and utilization of services provided by CHWs. To understand community perceptions of the quality of care in an iCCM intervention in western Kenya, we used the Primary Care Assessment Survey to compare caregiver attitudes about the diagnosis and treatment of childhood pneumonia as provided by CHWs and facility-based health workers (FBHWs). Overall, caregivers rated CHWs more highly than FBHWs across a set of 10 domains that capture multiple dimensions of the care process. Caregivers perceived CHWs to provide higher quality care in terms of accessibility and patient relationship and equal quality care on clinical aspects. These results argue for the continued implementation and scale-up of iCCM programs as an acceptable intervention for increasing access to treatment of childhood pneumonia.

Introduction

Global under-five mortality has greatly declined over the last two decades. To accelerate progress in reducing under-five child mortality, the World Health Organization (WHO) and the United Nations International Children's Emergency Fund (UNICEF) have recommended the adoption of integrated community case management (iCCM) programs targeting the three major infectious killers of children under 5 years—diarrhea, malaria, and pneumonia—to decrease mortality by 70%, 60%, and 90%, respectively, for these conditions.13 Though traditionally community health workers (CHWs) have been used to deliver a variety of services including health education, maternal health counseling, and medication monitoring (e.g., directly observed therapy),4 there has been an increasing emphasis on expanding the role of CHWs to address health workforce deficiencies. iCCM trains lay CHWs to assess, classify, and treat uncomplicated cases of diarrhea, malaria, and pneumonia and refer complicated or severe cases in areas that lack access to prompt and effective treatment due to patient level barriers such as lack of affordable transportation to the health facility, and health system level barriers including both direct and indirect costs.3

The implementation of iCCM has yielded mixed results in its impact on child pneumonia mortality. Early reports of the efficacy of community management of pneumonia in resource-limited settings were promising with a meta-analysis from 1992 (and subsequent reanalysis using primary data in 2003) showing a statistically significant 30% decrease in total under-five mortality in studies mostly from Asia.5,6 Later studies have validated that many iCCM programs incorporating pneumonia care performed well on process measures711 and outcomes12 in the sub-Saharan African context. However, other research has shown that many iCCM programs have not achieved decreases in mortality and fail to perform on intermediate outcomes.1316 Especially, troubling is the result of a study in which adding pneumonia management to an existing program of diarrhea and malaria community management led to no statistically significant reduction in mortality in a well-controlled randomized controlled trial.15 Therefore, it is imperative to perform research that assesses the efficacy and acceptability of iCCM programs.

African policy makers have been hesitant to integrate pneumonia care into the CHW repertoire. In 2014, only 27 of 42 sub-Saharan African countries surveyed were providing “complete” iCCM compared with 35 providing CCM for diarrhea and 32 for malaria.17 A recent meta-analysis showed that one of the most important aspects of scalable interventions with CHWs is community acceptance.18 Although some studies have demonstrated that iCCM interventions are acceptable to the community,19,20 others have shown that programs are resisted if CHWs do not provide services of value.21 This is important because iCCM programs, which have low utilization and likely low acceptance of services are the least cost-effective, do not lead to decreases in mortality, and may decrease demand for biomedical health care, leading the most marginalized to seek care from ineffective providers.1,22 In the current study, we sought to determine the level of community acceptance of CHWs capacity to diagnose and treat sick children with pneumonia at the community level when compared with facility-based health-care workers in western Kenya. Building on the work of other groups in East Africa,23 we used an adapted version of the Primary Care Assessment Survey (PCAS)24 to evaluate perceptions of caregivers who sought medical attention for their children with pneumonia.

Materials and Methods

Study design.

The current study was a cross-sectional survey of caregivers of children aged 2–59 months visiting CHWs and facility-based health workers (FBHWs) for management of pneumonia (fast breathing and lower chest in-drawing). It was nested within an implementation science project occurring in Homabay County, Kenya, in which CHWs were trained to administer oral rehydration salts and zinc for diarrhea, artemisinin combination therapy for malaria, and oral amoxicillin for pneumonia (fast breathing and chest in-drawing). This parent study was commissioned by the Kenya Ministry of Health, supported by the WHO and UNICEF, and registered as ACTRN12614000208606.

Setting.

The study was conducted between June and August 2014 in Homabay County in western Kenya. Homabay County has six administrative subcounties: Homa Bay, Ndhiwa, Mbita, Suba, South Rachuonyo, and North Rachuonyo. It is a rural county with a population of approximately one million. Children under 5 years account for 16% of the population.25 Under-five mortality in Homabay is 130/1,000 compared with the Nyanza average of 91/1,000.26 The most serious barriers to the availability of child health services in Homabay are related to inadequate human resources. These include prolonged waiting times, poor communication between staff and patients, and negative previous experiences.27 Despite an adequate number of health facilities, Homabay county suffers from inequities in health worker distribution. Even though there are an average of four doctors and 51 nurses per 100,000 populations, 58% of residents have to travel at least 5 km to the nearest health facility.2830 To address the inequitable provision of services and the high under-five mortality, Homabay was selected to receive an iCCM intervention. Homabay has implemented the community strategy for primary care with full coverage of community health units including over 2,600 CHWs and 200 community health extension workers (CHEWs) who have been trained in iCCM. Each CHW covers 50–100 households while 10–20 CHWs are supervised by one CHEW.29

Participants.

Study participants were caregivers whose children, aged 2–59 months, had received treatment of pneumonia from a CHW or FBHW in the past 8 weeks. To identify caregivers of children treated by CHWs, we used an online registry that tracked all CHW diagnosis, care, and treatment of children. For FBHW treated children, facility-based registers were reviewed. Caregivers were then traced by trained research assistants who also administered surveys.

Sample size.

Estimates of the attainable sample size and power calculations for this study were based on historical data from the iCCM program with a pneumonia prevalence of 8.6% and a monthly incidence of 2.0%. Approximately 130 children with pneumonia are seen in the community per month per subcounty in this program. The estimated sample size was 392 caregivers whose children were treated by CHWs and FBHWs with an equal number (196) in each category. This sample size gave us 80% power to be able to detect a 15% difference between perceived quality of care between CHWs and FBHWs.

Sampling.

Eligible caregivers from both the online and facility-based registers were purposively sampled and asked to participate in a one-on-one quantitative interview. Facilities were matched to community units from which caregivers who sought treatment at CHWs were sampled.

Data collection.

We used the PCAS instrument to collect data. The PCAS is a validated tool comprised of Likert-scale questions designed to assess the attitudes of patients and caregivers of patients towards primary care practitioners in a number of domains.24 Trained research assistants administered the surveys in the preferred language of the caregiver (either Dholuo, Kiswahili, or English). To minimize bias, the same research assistant administered both the CHW and FBHW surveys when possible.

Main outcome variables.

The main outcome of this study is perceived quality of care as measured by the PCAS. Previous studies have shown that a high perceived quality of care is associated with an increased utilization of services and therefore acceptability.31 The PCAS measures caregivers' perceptions of the quality of primary care through 10 different domains, including detailed measurement of the provider-patient relationship (communication quality, patient trust, provider knowledge of patient, interpersonal treatment, and relationship duration). For this study, we have grouped these 10 domains into three general categories of accessibility, clinical care, and patient relationships (Table 1). The category of accessibility includes the domains of organizational access, financial access, visit-based continuity, and longitudinal continuity. The category of clinical care includes the domains of preventive counseling (measured by number of health messages delivered) and physical examination. The category of patient relationship includes the domains of interpersonal treatment, communication, trust, and patient knowledge. In addition, two summary scale variables were assessed: the self-reported satisfaction of the caregiver and a domain summary that is an average of all domains excluding longitudinal continuity due to heterogeneity of this variable due to surveyor error.

Table 1

PCAS domain score definitions

CategoryDomain scaleContent
AccessibilityOrganizational accessAvailability of staff and services and convenience of location of health services
Financial accessMeasure of the amount of money spent on treatment
Longitudinal continuityDuration of contact between health provider and client
Visit-based continuityOngoing care for the same period of illness
Clinical carePreventive counselingDiscussion of preventive measures with client
Physical examinationThoroughness of physical examination
Patient relationshipCommunicationAbility to probe for symptoms, give feedback and assist in making treatment decisions
Interpersonal treatmentPatience, friendliness, respect of patient, and giving quality time to a patient
TrustIntegrity and role of provider as patient's agent
Patient knowledgeProvider knowledge of patient
Summary scoresSelf-reported satisfactionCaregivers overall satisfaction with the visit
Domain summaryAverage score across all domains

PACS = Primary Care Assessment Survey.

Statistical methods.

PCAS domain raw scores were calculated, missing scores imputed, and scaled scores calculated using guidelines from the original PCAS study.24 Missing scores were imputed for all domains where at least 50% of their total component questions were answered. The mean score of the completed questions was assumed for the missing components and an imputed score was calculated. Sociodemographic variables were analyzed by performing statistical tests for all variables between the CHW and FBHW groups. Principle component analysis based on assets was used to compute the socioeconomic status (SES) of the surveyed respondents as previously described.32

Comparisons of PCAS domain-scaled scores were performed using Wilcoxon–Mann–Whitney test to compare medians between CHW and FBHW provided care. A model was constructed to examine difference in domain ratings between CHW and FBHW provided care while controlling for possible confounders. The factors of time since last visit, SES, caregiver education, caregiver sex, and geographic location were determined as covariates a priori to include in this analysis. Domain scores were dichotomized using a median split and a modified Poisson regression with robust error variance was used to determine incidence rate ratios (IRRs) for receiving “high” domain scores given CHW care. IRRs greater than one suggest CHW superiority, values equal to one suggest equivalence between CHWs and FBHWs, and values less than one suggest FBHW superiority. This method was preferred over logistic regression as the outcomes were, by definition, nonrare.33

Ethical clearance.

The study protocol was reviewed and approved by the Kenya Medical Research Institute National Ethical Review Committee, as well as the University of California, San Francisco Committee for Health Research. Written consent in the preferred local language was obtained from caregivers of children prior to any study procedure.

Results

Caregivers selected from all six subcounties of Homabay participated in the study with 194 receiving care from a CHW and 174 receiving care from an FBHW. Two surveys from the CHW and six in the FBHW group and were excluded due to incomplete data caused by a communication error with our survey software. In addition, one survey in the FBHW group was excluded due to the child being older than 59 months. This yielded a total of 192 surveys in the CHW group and 167 in the FBHW group that were analyzed. Of the overall sample, 157/192 (82%) of the CHW group and 101/167 (61%) of the FBHW group contained data for all domain score variables. In both groups, incomplete data were mostly due to missing data for the longitudinal continuity domain with 35 missing in the CHW and 56 missing in the FBHW groups. Data were imputed for domain scores in 22/192 (12%) of the CHW group and 34/167 (20%) of the FBHW group. This difference was statistically significant by χ2 test (P < 0.02).

Sociodemographic characteristics and access indicators.

As shown in Table 2, characteristics of caregivers and children were similar across both groups in terms of caregiver sex, caregiver age, caregiver education, SES, child sex, and child age. Differences were seen in the relationship of the caregiver to the child (P < 0.004), caregiver religion (P < 0.002), and father's occupation (P < 0.022) by χ2 tests.

Table 2

Sociodemographic characteristics of caregivers and children

CharacteristicCHW care, n (%)FBHW care, n (%)P value
Caregiver sex0.827
 Female176 (92)152 (91)
 Male16 (8)15 (9)
 Total192167
Caregiver age mean (SD)29 (8.2)29.3 (9.1)0.924
 Total191167
Caregiver relation0.004
 Mother173 (90)132 (79)
 Father12 (6)14 (8)
 Other7 (4)21 (13)
 Total192167
Caregiver religion0.002
 Christian159 (83)155 (93)
 Traditional21 (11)7 (4)
 Muslim3 (1)0 (0)
 Other9 (5)5 (3)
 Total192167
Socioeconomic status0.250
 Lower 1/367 (36)47 (31)
 Middle 1/365 (35)48 (31)
 Upper 1/355 (29)58 (38)
 Total187153
Caregiver education0.374
 Some primary136 (71)110 (66)
 Secondary48 (25)45 (26)
 University/College2 (1)6 (4)
 Other6 (3)6 (4)
 Total192167
Father's occupation0.022
 Day laborer32 (17)23 (14)
 Farmer68 (35)37 (22)
 Fisherman14 (7)15 (9)
 Institutional Employee8 (4)8 (5)
 Small Businessman28 (15)31 (19)
 Unemployed17 (9)33 (19)
 Other25 (13)20 (12)
 Total192167
Child sex0.714
 Female94 (49)85 (51)
 Male98 (51)82 (49)
 Total192167
Child age (months)0.207
 2–1258 (31)37 (23)
 13–3690 (48)81 (50)
 36–6040 (21)43 (26)
 Total188161
Child symptomsN/A
 Cough192 (100)162 (97)
 Fever153 (80)141 (84)
 Fast breathing124 (65)135 (81)
 Watery stools27 (14)15 (9)
 Other9 (5)22 (13)

CHW = community health worker; FBHW = facility-based health worker; NA = not applicable; SD = standard deviation.

Caregivers whose children received care from CHWs showed statistically significant improved access to care from their health professional across a number of indicators (Table 3) including travel time (P < 0.001), operating hours (P < 0.001), waiting time (P < 0.001), expense of the visit (P < 0.002), and expense of the drugs (P < 0.001).

Table 3

Access indicators

CharacteristicCHW, n (%)FBHW, n (%)P value
Travel time< 0.001
 < 30 minutes163 (85)44 (26)
 0.5–1 hours27 (14)91 (55)
 1–2 hours2 (1)28 (17)
 > 2 hours0 (0)4 (2)
 Total192167
More operating hours needed< 0.001
 No131 (71)44 (27)
 Yes54 (29)116 (73)
 Total185160
Waiting time< 0.001
 None120 (63)6 (4)
 < 5 minutes59 (31)14 (8)
 6–30 minutes13 (7)112 (68)
 > 30 minutes0 (0)34 (20)
 Total192166
Visit expensive?0.002
 No174 (91)127 (80)
 Yes17 (9)33 (20)
 Total191160
Drugs skipped due to cost?< 0.001
 No191 (99)142 (85)
 Yes1 (1)24 (15)
 Total192167

CHW = community health worker; FBHW = facility-based health worker.

Bivariate analysis: differences in perceived quality of care between CHW and FBHW care.

Differences in all domains were statistically significant in all cases (P < 0.001 for all comparisons) with CHWs being rated more highly than FBHWs. Larger differences in means were seen in variables related to access to care and patient relationships than in clinical care (Table 4).

Table 4

Bivariate analysis: differences in perceived quality of care between CHW and FBHW care

CharacteristicCHW, mean (SD)CHW, median (IQR)FBHW, mean (SD)FBHW, median (IQR)P value*
Financial access90 (11)100 (80–100)44 (25)40 (20–60)< 0.001
Organizational access82 (13)80 (73–93)46 (24)40 (27–60)< 0.001
Visit-based continuity97 (10)100 (100–100)75 (25)80 (60–100)< 0.001
Longitudinal continuity75 (25)75 (50–100)54 (24)50 (50–75)< 0.001
Patient knowledge77 (13)77 (69–85)64 (23)64 (44–77)< 0.001
Preventive counseling87 (18)100 (67–100)75 (31)100 (67–100)< 0.001
Physical examination79 (14)80 (60–80)68 (23)60 (60–80)< 0.001
Communication81 (12)81 (75–90)67 (20)63 (52–83)< 0.001
Interpersonal treatment83 (10)80 (80–88)65 (21)60 (48–80)< 0.001
Trust77 (10)75 (71–82)73 (12)71 (64–82)< 0.001
Domain summary84 (7)83 (79–88)65 (16)65 (54–75)< 0.001
Self-reported satisfaction88 (12)80 (80–100)78 (19)80 (60–100)< 0.001

CHW = community health worker; FBHW = facility-based health worker; IQR = interquartile range; SD = standard deviation.

All P values are based on the Wilcoxon–Mann–Whitney comparison of medians.

Poisson regression model: differences in perceived quality of care between CHW and FBHW care.

Our multivariate analysis using a more stringent modified Poisson regression (Table 5) showed that CHWs still outperformed FHBWs in most areas with IRRs greater than one, indicating a higher perceived quality of care for CHWs. CHWs were rated more highly in terms of financial access (IRR: 7.15, 95% confidence interval [CI]: 4.65–11.00, P < 0.001), organizational access (IRR: 4.92, 95% CI: 3.55–6.80, P < 0.001), self-reported satisfaction (IRR: 1.62, 95% CI: 1.34–1.97, P < 0.001), and the domain summary (IRR: 1.50, 95% CI: 1.43–1.59, P < 0.001). However, the outcomes related to the provision of clinical care—preventive counseling (IRR: 1.33, 95% CI: 0.96–1.83, P = 0.081) and physical examination (IRR: 1.18, 95% CI: 0.93–1.50, P = 0.170)—showed no statistically significant difference between groups.

Table 5

Poisson regression model: differences in perceived quality of care between CHW and FBHW care

CharacteristicUnadjusted IRR* (CI)P valueAdjusted IRR (CI)P value
Financial access7.73 (4.90–12.20)< 0.0017.15 (4.65–11.00)< 0.001
Organizational access5.09 (3.61–7.18)< 0.0014.92 (3.55–6.80)< 0.001
Visit-based continuity2.04 (1.44–2.90)< 0.0012.31 (1.63–3.29)< 0.001
Longitudinal continuity2.38 (1.63–3.46)< 0.0012.30 (1.57–3.36)< 0.001
Patient knowledge2.26 (1.76–2.91)< 0.0012.44 (1.95−3.05)< 0.001
Preventive counseling1.23 (0.88–1.72)0.2181.33 (0.96–1.83)0.081
Physical examination1.20 (0.93–1.56)0.1531.18 (0.93–1.50)0.170
Communication1.98 (1.57–2.50)< 0.0011.91 (1.53–2.38)< 0.001
Interpersonal treatment2.21 (1.69–2.90)< 0.0012.10 (1.63–2.71)< 0.001
Trust1.30 (1.05–1.62)0.0151.32 (1.07−1.63)0.010
Domain summary1.49 (1.41–1.59)< 0.0011.50 (1.43–1.59)< 0.001
Self-reported satisfaction1.63 (1.34–1.99)< 0.0011.62 (1.34–1.97)< 0.001

CHW = community health worker; CI = confidence interval; FBHW = facility-based health worker; IRR = incidence rate ratio.

IRR is the probability of being in the top 50% of all scores given seeking care from a CHW. Therefore, IRRs above one suggest CHW superiority, IRRs at one suggest equivalence between CHWs and FBHWs, and IRRs below one suggest FBHW superiority. The adjusted model controls for time since last visit, socioeconomic status, caregiver education, caregiver sex, and geographic location.

Discussion

The data presented here allows for a robust examination of community perception of quality of pneumonia home case management in western Kenya. Overall, caregivers rated the quality of CHW provided home-based management for childhood pneumonia higher than FBHW provided care.

Caregivers rated CHWs higher in regards to ease of access. This is likely because of both the spatial distribution of CHWs, as they live in the community and therefore are closer to clients, and the fact that CHWs do not charge user fees for care or medications. Studies have found that utilization of health-care services decreases with increasing travel time and cost of services.34,35 Though Kenya has implemented a policy to decrease user fees,36 especially for the poorest Kenyans, there is a lack of adherence to this policy.37 And there are still many indirect costs associated with seeking care from a health facility such as the cost of transportation, food, and foregone work.35 Home case management by well-trained well-supplied CHWs may be one way to expand access to care to this population. Though we found no difference in SES between the caregivers who used CHWs and FBHWs to access care, CHWs were rated highly in accessibility across all income levels (data not shown) arguing that economically vulnerable populations consider them accessible.

CHWs were rated more highly than FBHWs in their ability to communicate with caregivers and instill trust. Patients answered positively when asked about the integrity, friendliness, and support in decision-making by CHWs. The ability to enter a therapeutic relationship with the patient is important as both fear of stigma and perception of poor quality care were associated with decreased utilization of iCCM in Ethiopia.38 This high satisfaction with CHWs is consistent with task shifting literature in human immunodeficiency virus (HIV), which has found that clients receiving treatment from less trained staff are highly satisfied with their care as they feel more supported by providers that are more relatable.39 In addition, more trust in providers is associated with better adherence to medication for chronic conditions such as hypertension.40 Therefore, CHWs may play an important role in ensuring that caregivers follow recommendations for medical treatment of their children. This is consistent with a recent study in Ethiopia that found adherence rates of 84% for trimethoprim/sulfamethoxazole prescriptions dispensed by CHWs.41 Antibiotic resistance is a concern both in the in setting of home-based treatment of pneumonia as well as clinic prescribed therapy.42 However, resistance levels will be lower if all courses of antibiotics are completed due to high adherence rates.43

In the present study, CHWs delivered a similar number of counseling messages compared with FBHWs. Studies in other areas, such as sex education, have established the role of peers in helping to set norms even when they are less expert on an issue.44 The idea of a trusted CHW peer being the most appropriate conveyor of health education and counseling messages is not new.4 However, continued study of the effect of increasing professionalization of CHWs on their ability to relate to community members and provide effective peer counseling will be necessary moving forward.

Even in regards to clinical skills, the area in which FBHWs have a clear advantage, caregivers rated CHWs and FBHWs equally. Though a lack of clinical skill is one of the main reasons cited by professional health workers not to support task shifting,45,46 caregivers did not perceive such a decrease in care quality. One explanation could be that CHWs simply spend more time with the patients and are therefore able to perform a more thorough evaluation. In the environment of a busy clinic, trained health professionals often spend very little time with the patient. One study of a health center in Kenya showed that of a 2 hour 25 minute total clinic visit (including wait time, check in and time with the clinician), less than 10 minutes was actually spent with a clinician.47 From a patient's perspective, this would stand in stark contrast to a visit with a CHW, where the entirety of the time was spent with the provider. In addition, it has been shown that FBHWs often do not adhere to the Integrated Management of Childhood Illness (IMCI) guidelines (which parallel iCCM guidelines) due to either a lack of belief in their validity or “cognitive overload” due to time pressure.48 Mature iCCM programs have achieved a consistency with guidelines of approximately 70%, whereas studies of IMCI in a variety of facilities have only demonstrated a maximum of 30% consistency.4850 Therefore, caregiver faith in CHW ability may be well placed.

In terms of overall satisfaction, CHWs were preferred to FBHWs when examining either a self-reported satisfaction score (a component of the PCAS) or a summary score that was calculated as the mean across all PCAS domains indicating acceptability. This is in line with many other studies that have shown the acceptability of community case management of disease starting with diarrhea and malaria5153 and more recent research on iCCM including pneumonia care.19,20 This is likely because the CHWs in this program have been providing services which are considered valuable to the community.21 Previous work has demonstrated the availability of drugs as an exceedingly important component of iCCM interventions. If CHWs are not adequately supplied, the community sees them as useless.14 In addition, conflicts can arise between health facilities and CHWs if they are receiving drugs from a common source, with the result often being that CHWs are forced to go without.54 In the current study, the supply of amoxicillin was highly prioritized (with sufficient stock given to both facilities and CHWs) to limit stockouts and may have contributed to the perceived utility of these CHWs—they were able to perform the duties expected of them by the community.

Finally, individuals who sought care with CHWs were more likely to practice African traditional religion. This is noteworthy as previous work has shown that members of this group are less likely to access care for a variety of conditions.55,56 This may be because some African traditional religions place stigma on seeking biomedical health care.55 The ability to discreetly seek care from a CHW may ameliorate this barrier as it can be seen as simply talking to a neighbor rather than receiving biomedical treatment. This is analogous to previous efforts to encourage exclusive breast-feeding for HIV-positive women as a means to prevent vertical transmission so that they are able to be more circumspect about revealing their status.57 Therefore, CHWs may be an effective way to increase the provision of biomedical care to individuals otherwise wary of it.

The strength of this study was the evaluation of specifically community case management of pneumonia in a population of CHWs implementing community case management of malaria and diarrhea. Limitations to this study include an inability to qualitatively describe differences in ratings between CHW and FBHW provided care. A mixed methods approach may have yielded more robust data. In addition, cross sectional studies have an inherent tendency to exhibit bias because of systematic differences between groups. However, we attempted to mitigate this by matching our data both spatially and temporally. The data from this study were collected by program research assistants and therefore may have suffered from desirability bias. However, because the same individuals administered both the CHW and FBHW surveys this potential bias should be equally distributed. Though all cases of pneumonia treated by CHWs met previously defined iCCM diagnostic criteria, the cases treated by FBHWs were identified solely by facility register review. This could mean there were clinical differences between the two groups. However, there were no serious adverse events (such as death) in either group, and children's symptoms were similar in both group (Table 2). In addition, the purpose of the study was only to determine caregiver satisfaction, therefore the effect of this difference in case identification on outcomes of interest was likely small. Finally, caregivers were only asked to participate in the study if their children had received care in the past 8 weeks to reduce recall bias.

Overall, this study presents a strong case for the implementation and scale-up of the treatment of pneumonia as part of iCCM. Caregivers of children under 5 years find CHW provided care for pneumonia both readily accessible and of high quality. By increasing access to lifesaving pneumonia care in a culturally sensitive way in the most under-resourced settings, large impacts on under-five mortality may be achieved.

ACKNOWLEDGMENTS

We acknowledge and thank Nicholas Oliphant of United Nations International Children's Emergency Fund for his expert review of this manuscript. We also thank the integrated community case management administrative staff, Phosa Adhiambo and Evelyn Siaga, and our research assistants and subcounty coordinators for all of their hard work in making this research possible. We also thank Kenya Medical Research Institute and University of California, San Francisco for allowing this research to take place. Finally, we graciously thank all of the participants for their time and input on this important question.

  • 1.

    Young M, Wolfheim C, Marsh DR, Hammamy D, 2012. World Health Organization/United Nations Children's Fund joint statement on integrated community case management: an equity-focused strategy to improve access to essential treatment services for children. Am J Trop Med Hyg 87 (Suppl): 610.

    • Search Google Scholar
    • Export Citation
  • 2.

    UN Interagency Group for Child Mortality Estimation, 2014. Levels and Trends in Child Mortality New York, NY: UNICEF.

  • 3.

    Marsh DR, Hamer DH, Pagnoni F, Peterson S, 2012. Introduction to a special supplement: evidence for the implementation, effects, and impact of the integrated community case management strategy to treat childhood infection. Am J Trop Med Hyg 87 (Suppl): 25.

    • Search Google Scholar
    • Export Citation
  • 4.

    Lewin S, Munabi-Babigumira S, Glenton C, Daniels K, Bosch-Capblanch X, van Wyk BE, Odgaard-Jensen J, Johansen M, Aja GN, Zwarenstein M, Scheel IB, 2010. Lay health workers in primary and community health care for maternal and child health and the management of infectious diseases. Cochrane Database Syst Rev (3) CD004015.

    • Search Google Scholar
    • Export Citation
  • 5.

    Sazawal S, Black RE, 1992. Meta-analysis of intervention trials on case-management of pneumonia in community settings. Lancet 340: 528533.

    • Search Google Scholar
    • Export Citation
  • 6.

    Sazawal S, Black RE; Pneumonia Case Management Trials Group, 2003. Effect of pneumonia case management on mortality in neonates, infants, and preschool children: a meta-analysis of community-based trials. Lancet Infect Dis 3: 547556.

    • Search Google Scholar
    • Export Citation
  • 7.

    Hamer DH, Brooks ET, Semrau K, Pilingana P, MacLeod WB, Siazeele K, Sabin LL, Thea DM, Yeboah-Antwi K, 2012. Quality and safety of integrated community case management of malaria using rapid diagnostic tests and pneumonia by community health workers. Pathog Glob Health 106: 3239.

    • Search Google Scholar
    • Export Citation
  • 8.

    Seidenberg PD, Hamer DH, Iyer H, Pilingana P, Siazeele K, Hamainza B, MacLeod WB, Yeboah-Antwi K, 2012. Impact of integrated community case management on health-seeking behavior in rural Zambia. Am J Trop Med Hyg 87 (Suppl): 105110.

    • Search Google Scholar
    • Export Citation
  • 9.

    Kalyango JN, Rutebemberwa E, Alfven T, Ssali S, Peterson S, Karamagi C, 2012. Performance of community health workers under integrated community case management of childhood illnesses in eastern Uganda. Malar J 11: 282.

    • Search Google Scholar
    • Export Citation
  • 10.

    Kalyango JN, Alfven T, Peterson S, Mugenyi K, Karamagi C, Rutebemberwa E, 2013. Integrated community case management of malaria and pneumonia increases prompt and appropriate treatment for pneumonia symptoms in children under five years in eastern Uganda. Malar J 12: 340.

    • Search Google Scholar
    • Export Citation
  • 11.

    Kalyango JN, Rutebemberwa E, Karamagi C, Mworozi E, Ssali S, Alfven T, Peterson S, 2013. High adherence to antimalarials and antibiotics under integrated community case management of illness in children less than five years in eastern Uganda. PLoS One 8: e60481.

    • Search Google Scholar
    • Export Citation
  • 12.

    Mugeni C, Levine AC, Munyaneza RM, Mulindahabi E, Cockrell HC, Glavis-Bloom J, Nutt CT, Wagner CM, Gaju E, Rukundo A, Habimana JP, Karema C, Ngabo F, Binagwaho A, 2014. Nationwide implementation of integrated community case management of childhood illness in Rwanda. Glob Health Sci Pract 2: 328341.

    • Search Google Scholar
    • Export Citation
  • 13.

    Kelly JM, Osamba B, Garg RM, Hamel MJ, Lewis JJ, Rowe SY, Rowe AK, Deming MS, 2001. Community health worker performance in the management of multiple childhood illnesses: Siaya District, Kenya, 1997–2001. Am J Public Health 91: 16171624.

    • Search Google Scholar
    • Export Citation
  • 14.

    Nsona H, Mtimuni A, Daelmans B, Callaghan-Koru JA, Gilroy K, Mgalula L, Kachule T, Zamasiya T, 2012. Scaling up integrated community case management of childhood illness: update from Malawi. Am J Trop Med Hyg 87 (Suppl): 5460.

    • Search Google Scholar
    • Export Citation
  • 15.

    Chinbuah MA, Kager PA, Abbey M, Gyapong M, Awini E, Nonvignon J, Adjuik M, Aikins M, Pagnoni F, Gyapong JO, 2012. Impact of community management of fever (using antimalarials with or without antibiotics) on childhood mortality: a cluster-randomized controlled trial in Ghana. Am J Trop Med Hyg 87 (Suppl): 1120.

    • Search Google Scholar
    • Export Citation
  • 16.

    Miller NP, Amouzou A, Tafesse M, Hazel E, Legesse H, Degefie T, Victora CG, Black RE, Bryce J, 2014. Integrated community case management of childhood illness in Ethiopia: implementation strength and quality of care. Am J Trop Med Hyg 91: 424434.

    • Search Google Scholar
    • Export Citation
  • 17.

    Rasanathan K, Muñiz M, Bakshi S, Kumar M, Solano A, Kariuki W, George A, Sylla M, Nefdt R, Young M, Diaz T, 2014. Community case management of childhood illness in sub-Saharan Africa—findings from a cross-sectional survey on policy and implementation. J Glob Health 4: 020401.

    • Search Google Scholar
    • Export Citation
  • 18.

    Pallas SW, Minhas D, Pérez-Escamilla R, Taylor L, Curry L, Bradley EH, 2013. Community health workers in low-and middle-income countries: what do we know about scaling up and sustainability? Am J Public Health 103: e74e82.

    • Search Google Scholar
    • Export Citation
  • 19.

    Buchner DL, Brenner JL, Kabakyenga J, Teddy K, Maling S, Barigye C, Nettel-Aguirre A, Singhal N, 2014. Stakeholders' perceptions of integrated community case management by community health workers: a post-intervention qualitative study. PLoS One 9: e98610.

    • Search Google Scholar
    • Export Citation
  • 20.

    Nanyonjo A, Nakirunda M, Makumbi F, Tomson G, Kallander K; inSCALE Study Group, 2012. Community acceptability and adoption of integrated community case management in Uganda. Am J Trop Med Hyg 87 (Suppl): 97104.

    • Search Google Scholar
    • Export Citation
  • 21.

    Delacollette C, Van der Stuyft P, Molima K, 1996. Using community health workers for malaria control: experience in Zaire. Bull World Health Organ 74: 423.

    • Search Google Scholar
    • Export Citation
  • 22.

    Collins D, Jarrah Z, Gilmartin C, Saya U, 2014. The costs of integrated community case management (iCCM) programs: a multi-country analysis. J Glob Health 4: 020407.

    • Search Google Scholar
    • Export Citation
  • 23.

    Nanyonjo A, Makumbi F, Etou P, Tomson GR, Kallander K; inSCALE Study Group, 2013. Perceived quality of care for common childhood illnesses: facility versus community based providers in Uganda. PLoS One 8: e79943.

    • Search Google Scholar
    • Export Citation
  • 24.

    Safran DG, Kosinski M, Tarlov AR, Rogers WH, Taira DH, Lieberman N, Ware JE, 1998. The Primary Care Assessment Survey: tests of data quality and measurement performance. Med Care 36: 728739.

    • Search Google Scholar
    • Export Citation
  • 25.

    Population Action International, 2014. Population Dynamics, Environment, and Sustainable Development in Homa Bay County Available at: http://pai.org/wp-content/uploads/2014/07/PAI_HomaBay-3.pdf. Accessed May 3, 2015.

    • Search Google Scholar
    • Export Citation
  • 26.

    Kenya National Bureau of Statistics, 2013. Nyanza Province Multiple Indicator Cluster Survey 2011, Final Report. Nairobi, Kenya: Kenya National Bureau of Statistics.

    • Search Google Scholar
    • Export Citation
  • 27.

    Bedford KJA, Sharkey AB, 2014. Local barriers and solutions to improve care-seeking for childhood pneumonia, diarrhoea and malaria in Kenya, Nigeria, and Niger: a qualitative study. PLoS One 9: e100038.

    • Search Google Scholar
    • Export Citation
  • 28.

    Health Policy Project, 2013. Homabay County: Health at a Glance. Available at: http://www.healthpolicyproject.com/pubs/291/Homa%20Bay%20County-FINAL.pdf. Accessed May 3, 2015.

    • Search Google Scholar
    • Export Citation
  • 29.

    Kenya Ministry of Health, 2013. A National Framework and Plan of Action for Implementation of Integrated Community Case Management (iCCM) in Kenya, 2013–2018. Nairobi, Kenya: Kenya Ministry of Health.

    • Search Google Scholar
    • Export Citation
  • 30.

    Otien SO, Macharia D, 2014. Factors influencing utilization of health services in Kenya: the case of Homa Bay County. IJPHS 3: 213223.

  • 31.

    Fotso JC, Mukiira C, 2012. Perceived quality of and access to care among poor urban women in Kenya and their utilization of delivery care: harnessing the potential of private clinics? Health Policy Plan 27: 505515.

    • Search Google Scholar
    • Export Citation
  • 32.

    Filmer D, Pritchett LH, 2001. Estimating wealth effects without expenditure data—or tears: an application to educational enrollments in states of India. Demography 38: 115132.

    • Search Google Scholar
    • Export Citation
  • 33.

    Zou G, 2004. A modified Poisson regression approach to prospective studies with binary data. Am J Epidemiol 159: 702706.

  • 34.

    Tanser F, Gijsbertsen B, Herbst K, 2006. Modelling and understanding primary health care accessibility and utilization in rural South Africa: an exploration using a geographical information system. Soc Sci Med 63: 691705.

    • Search Google Scholar
    • Export Citation
  • 35.

    Ensor T, 2004. Overcoming barriers to health service access: influencing the demand side. Health Policy Plan 19: 6979.

  • 36.

    Chuma J, Musimbi J, Okungu V, Goodman C, Molyneux C, 2009. Reducing user fees for primary health care in Kenya: policy on paper or policy in practice? Int J Equity Health 8: 15.

    • Search Google Scholar
    • Export Citation
  • 37.

    Opwora A, Waweru E, Toda M, Noor A, Edwards T, Fegan G, Molyneux S, Goodman C, 2015. Implementation of patient charges at primary care facilities in Kenya: implications of low adherence to user fee policy for users and facility revenue. Health Policy Plan 30: 508517.

    • Search Google Scholar
    • Export Citation
  • 38.

    Tefera W, Tesfaye H, Bekele A, Kayessa E, 2014. Factors influencing the low utilization of curative child health services in Shebedino District, Sidama Zone, Ethiopia. Ethiop Med J 52 (Suppl 3): 109117.

    • Search Google Scholar
    • Export Citation
  • 39.

    Kredo T, Adeniyi FB, Bateganya M, Pienaar ED, 2014. Task shifting from doctors to non-doctors for initiation and maintenance of antiretroviral therapy. Cochrane Database Syst Rev 7: CD007331.

    • Search Google Scholar
    • Export Citation
  • 40.

    Abel WM, Efird JT, 2013. The association between trust in health care providers and medication adherence among black women with hypertension. Front Public Health 1: 66.

    • Search Google Scholar
    • Export Citation
  • 41.

    Najjemba R, Kiapi L, Demissie SD, Gossaye T, Engida M, Ratnayake R, Degefie T, Legesse H, Lemma AF, Getachew H, Gebrie M, 2014. Integrated community case management: quality of care and adherence to medication in Beneshangul-Gumuz Region, Ethiopia. Ethiop Med J 52 (Suppl 3): 8390.

    • Search Google Scholar
    • Export Citation
  • 42.

    Hamer DH, Marsh DR, Peterson S, Pagnoni F, 2012. Integrated community case management: next steps in addressing the implementation research agenda. Am J Trop Med Hyg 87 (Suppl): 151153.

    • Search Google Scholar
    • Export Citation
  • 43.

    Kardas P, 2002. Patient compliance with antibiotic treatment for respiratory tract infections, 2002. J Antimicrob Chemother 49: 897903.

    • Search Google Scholar
    • Export Citation
  • 44.

    Mellanby AR, Newcombe RG, Rees J, Tripp JH, 2001. A comparative study of peer-led and adult-led school sex education. Health Educ Res 16: 481492.

    • Search Google Scholar
    • Export Citation
  • 45.

    Owolabi OO, Glenton C, Lewin S, Pakenham-Walsh N, 2014. Stakeholder views on the incorporation of traditional birth attendants into the formal health systems of low-and middle-income countries: a qualitative analysis of the HIFA2015 and CHILD2015 email discussion forums. BMC Pregnancy Childbirth 14: 19.

    • Search Google Scholar
    • Export Citation
  • 46.

    Rustagi AS, Manjate RM, Gloyd S, John-Stewart G, Micek M, Gimbel S, Sherr K, 2015. Perspectives of key stakeholders regarding task shifting of care for HIV patients in Mozambique: a qualitative interview-based study with Ministry of Health leaders, clinicians, and donors. Hum Resour Health 13: 18.

    • Search Google Scholar
    • Export Citation
  • 47.

    Lynam PF, Smith T, Dwyer J, 1994. Client flow analysis: a practical management technique for outpatient clinic settings. Int J Qual Health Care 6: 179186.

    • Search Google Scholar
    • Export Citation
  • 48.

    Lange S, Mwisongo A, Mæstad O, 2014. Why don't clinicians adhere more consistently to guidelines for the integrated management of childhood illness (IMCI)? Soc Sci Med 104: 5663.

    • Search Google Scholar
    • Export Citation
  • 49.

    Ameha A, Karim AM, Erbo A, Ashenafi A, Hailu M, Hailu B, Folla A, Bizuwork S, Betemariam W, 2014. Effectiveness of supportive supervision on the consistency of integrated community cases management skills of the health extension workers in 113 districts of Ethiopia. Ethiop Med J 52 (Suppl 3): 6571.

    • Search Google Scholar
    • Export Citation
  • 50.

    Ahmed HM, Mitchell M, Hedt B, 2010. National implementation of integrated management of childhood illness (IMCI): policy constraints and strategies. Health Policy 96: 128133.

    • Search Google Scholar
    • Export Citation
  • 51.

    Ajayi IO, Falade CO, Olley BO, Yusuf B, Gbotosho S, Iyiola T, Olaniyan O, Happi C, Munguti K, Pagnoni F, 2008. A qualitative study of the feasibility and community perception on the effectiveness of artemether-lumefantrine use in the context of home management of malaria in south-west Nigeria. BMC Health Serv Res 8: 119.

    • Search Google Scholar
    • Export Citation
  • 52.

    Ajayi IO, Browne EN, Garshong B, Bateganya F, Yusuf B, Agyei-Baffour P, Doamekpor L, Balyeku A, Munguti K, Cousens S, Pagnoni F, 2008. Feasibility and acceptability of artemisinin-based combination therapy for the home management of malaria in four African sites. Malar J 7: 6.

    • Search Google Scholar
    • Export Citation
  • 53.

    Akweongo P, Agyei-Baffour P, Sudhakar M, Simwaka BN, Konaté AT, Adongo PB, Browne EN, Tegegn A, Ali D, Traoré A, Amuyunzu-Nyamongo M, Pagnoni F, Barnish G, 2011. Feasibility and acceptability of ACT for the community case management of malaria inurban settings in five African sites. Malar J 10: 240.

    • Search Google Scholar
    • Export Citation
  • 54.

    Callaghan-Koru JA, Hyder AA, George A, Gilroy KE, Nsona H, Mtimuni A, Bryce J, 2012. Health workers “and managers” perceptions of the integrated community case management program for childhood illness in Malawi: the importance of expanding access to child health services. Am J Trop Med Hyg 87 (Suppl): 6168.

    • Search Google Scholar
    • Export Citation
  • 55.

    Gyimah SO, Takyi BK, Addai I, 2006. Challenges to the reproductive-health needs of African women: on religion and maternal health utilization in Ghana. Soc Sci Med 62: 29302944.

    • Search Google Scholar
    • Export Citation
  • 56.

    Addai I, 2000. Determinants of use of maternal–child health services in rural Ghana. J Biosoc Sci 32: 115.

  • 57.

    Sibeko L, Coutsoudis A, Nzuza S, Gray-Donald K, 2009. Mothers' infant feeding experiences: constraints and supports for optimal feeding in an HIV-impacted urban community in South Africa. Public Health Nutr 12: 1983.

    • Search Google Scholar
    • Export Citation

Author Notes

* Address correspondence to Brian I. Shaw, School of Medicine, University of California, San Francisco, 513 Parnassus Avenue, S-245, San Francisco, CA 94143. E-mail: brian.shaw@ucsf.edu

Authors' addresses: Brian I. Shaw, School of Medicine, University of California, San Francisco, San Francisco, CA, E-mail: brian.shaw@ucsf.edu. Elijah Asadhi and Kevin Owuor, Center for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya, E-mails: easadhi@kemri-ucsf.org and kevinowuor1@gmail.com. Peter Okoth, Child Health, United Nations International Children's Emergency Fund, New York, NY, E-mail: pokoth@unicef.org. Mohamed Abdi, Center for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya, E-mail: mohasmail33@gmail.com. Craig R. Cohen, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, San Francisco, CA, E-mail: criag.cohen@ucsf.edu. Maricianah Onono, Center for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya, E-mail: maricianah@yahoo.com.

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